American Psychological Association 6th edition

Ordenshiya, K., & Revathi, G. (2025). A comparative study of traditional machine learning and hybrid fuzzy inference system machine learning models for air quality index forecasting. International Journal of Data Science and Analytics, 20(5), 4321-4342. https://doi.org/10.1007/s41060-025-00720-3

ISO-690 (author-date, English)

ORDENSHIYA, KM and REVATHI, GK, 2025. A comparative study of traditional machine learning and hybrid fuzzy inference system machine learning models for air quality index forecasting. International Journal of Data Science and Analytics. 1 October 2025. Vol. 20, no. 5, p. 4321-4342. DOI 10.1007/s41060-025-00720-3.

Modern Language Association 9th edition

Ordenshiya, K., and G. Revathi. “A Comparative Study of Traditional Machine Learning and Hybrid Fuzzy Inference System Machine Learning Models for Air Quality Index Forecasting”. International Journal of Data Science and Analytics, vol. 20, no. 5, Oct. 2025, pp. 4321-42, https://doi.org/10.1007/s41060-025-00720-3.

Mohr Siebeck - Recht (Deutsch - Österreich)

Ordenshiya, KM/Revathi, GK: A comparative study of traditional machine learning and hybrid fuzzy inference system machine learning models for air quality index forecasting, International Journal of Data Science and Analytics 2025, 4321-4342.

Emerald - Harvard

Ordenshiya, K. and Revathi, G. (2025), “A comparative study of traditional machine learning and hybrid fuzzy inference system machine learning models for air quality index forecasting”, International Journal of Data Science and Analytics, Vol. 20 No. 5, pp. 4321-4342.

Warning: These citations may not always be 100% accurate.